I am an experienced Data Science and Engineering leader focused on development of products and applications built on top of core ML/AI functionality. I have technical expertise in machine-learning and ML/analytics pipelines; LLM-based applications, and system modeling using deep-learning, probabilistic Bayesian inference, and simulation. I've worked across a variety of domains, including IoT, transportation/logistics, and agricultural/geospatial domains. I hold a Ph.D. in Ocean Physics from Columbia University and currently work as Senior Engineering Manager at bubble.io working on the development of AI-tools for the Bubble.io no-code application platform.
My professional experience spans industry and academia, with common threads around robust statistical modeling, ocean/weather/climate system modeling, and the development of novel analytical approaches that often leverage data synthesis across domains. I additionally have experience developing robust, scalable, and observable data-transformation and model-training pipelines.
Drawing on my background as an educator, I strive for clear communication, statistically- and physically- supported models and analyses, and growing and coaching high-performing data teams.